Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Detailed Action
Claims 127,128,130-138 and 140-150 are currently pending.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 04/03/2026 has been considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, an initialed and dated copy of Applicant's IDS form SB08 filed 04/03/2026 is attached to the instant Office action.
Response to Amendment
This action is in response to the Amendment filled on 04/03/2026. The amendment has been entered. Claims 129 and 139 are canceled earlier, and claims 130 and 132 have been amended. Claims 127,128,130-138 and 140-150 are pending, with claim 127 being independent in the instant application.
Response to Arguments
Applicant's Arguments/Remarks filed on 04/03/2026 on pages 6-8 regarding 35 U.S.C. 103 rejections have been fully considered and are found persuasive in view of the amended claims and presented Arguments/Remarks by the Applicants, specifically regarding the prior art Ranger. Examiner agrees with the Applicants that prior art Ranger doesn’t disclose "creating a compound model of internal and external features of the biological body segment …”, as recited in claim 127.
However, a new ground of rejections is necessitated by Applicant's claim amendments. Therefore, the previous rejections regarding 35 U.S.C.103 are being amended in this current office action. (See analysis below Claim Rejections-35 U.S.C. §103).
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham, v. John Deere Co., 383 U.S.1.148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
7. Claims 127,128,130-138,140,141,145-150 are rejected under 35 U.S.C. 103 as being unpatentable over an NPL Paper “Automated and Data-driven Computational Design of Patient-Specific Biomechanical Interfaces” by Kevin M. Moerman et al. (hereinafter Kevin, NPL published in 2016) in view of an NPL paper “Regional differences in pain threshold and tolerance of the transtibial residual limb: including the effects of age and interface material” by Winson Lee et al. (hereinafter Lee, Applicant mentioned about this reference in Spec. of current Application) and further in view of “3D reconstruction of the structure of a residual limb for customising the design of a prosthetic socket” by Zheng Shuxian et al. (hereinafter Zheng, NPL published in 2005).
Regarding claim 127, Kevin teaches a method of designing with a computer a biomechanical interface for a biological body segment, comprising: with a computer: generating a three-dimensional finite element analysis (FEA) model of the biomechanical interface (Kevin disclosed in page 1 under ‘Abstract’: “A patient-specific and data-driven computational framework for the automated design of biomechanical interfaces is presented here ... The proposed framework is presented for the application of transtibial amputee prostheses where the interface is formed by a prosthetic liner and socket.” It has been disclosed in page 3 under section II A.: “Fig. 3 presents an overview of the data-driven computational design framework. It illustrates how, based on MRI (Fig. 3A) and indentation tests (Fig. 3E), 3D and patient-specific FEA models can be constructed, which can be used to generate custom liner and socket designs.” It has been shown in Fig. 3 step (D), (F-J) that the liner and socket source geometries can be offset from the skin surface and can be meshed with the soft tissue to form a FEA model; spatially varying design features, such as socket compliance and fitting pressure, can be defined using FEA based measures of tissue vulnerability; fitting pressure fields can be used to morph the liner and socket into their desired shape, while also pre-loading the tissue due to donning; the designs can now be evaluated for body weight loading; and optimal designs is exported, for 3D printing based manufacturing. Therefore, Kevin teaches method of designing a biomechanical interface for a biological body segment (e.g., computational framework for the automated design of biomechanical interfaces is presented in the paper). A three-dimensional model of the biomechanical interface is generated in above disclosure (in Fig. 3, as an example)).
Kevin teaches defining, within the three-dimensional FEA model, an initial configuration of the biomechanical interface with an initial fitting pressure; (Examiner would construe the ‘initial fitting pressure’ in light of Spec. of current Application at para [00616]: “Once a configuration is identified for which a material region presents with the minimum stiffness, this configuration may serve, for that region, as the new initial or reference configuration.” Kevin disclosed in page 8 under section II H.: “The FEA based design and evaluation procedure consists of 5 steps which are schematically illustrated in Fig. 9 … The socket, liner, and tissue regions share nodes at each interface, simulating high friction tied interfaces. The liner and socket are each designed and donned in separate 2 step procedures. First fitting pressures are used to morph the geometries into desired designs. During the design phase the liner and socket are in a ‘ghosted” form i.e., they do not have significant stiffness and develop no significant stresses (hence shown as transparent in Fig. 9). … This process of morphing the designs (while the soft tissue is pre-loaded) without developing stresses in the liner or socket regions is achieved by modelling the liner and socket materials as multi-generational materials … Since during the design phase the material can be made to have negligible stiffness (γ = 1) they remain in an effectively stress free state when the source geometry is morphed into a desired design.” Therefore, Kevin teaches an initial configuration of the biomechanical interface being defined within the 3D FEA model, (e.g., during the FEA based design, the liner and socket do not have significant stiffness. Once their desired design is achieved, they are assigned with natural mechanical properties in a stress-free state and during the design phase the material can be made to have negligible stiffness (γ = 1) in an effectively stress free state when the source geometry is morphed into a desired design. The 3D patient-specific FEA models can be constructed, used to generate custom liner and socket designs (shown in Fig. 3).)).
Kevin teaches using the three-dimensional FEA model, simulating a dynamic use event to determine a loading pressure applied to at least one region of the biological body segment by the biomechanical interface in the initial configuration; (According to the dependent claim 150, the “dynamic use event is standing”, further as per claim 140 “the dynamic use event includes simulating a motion event performed in real-time by a subject”. Kevin disclosed in page 9-10 section IV: “This study presents a novel framework for the quantitative design, and computational evaluation, of patient-specific prosthetic liners and sockets for people with lower limb amputations. An overview of the components of the novel framework is presented in Fig. 3 … The design process is automated and driven by patient-specific data. The design is generated and evaluated using FEA. Evaluation is based on analysis of tissue loading during simulated standing on one leg, i.e. the application of a force equivalent to body weight.” In page 9 section III A. (left col.): “Fig. 3 shows the data-driven and automated design and computational modeling framework for development of patient-specific sockets and liners. For FEA the computational time for design and evaluation is currently 12 minutes”. The disclosure “FEA evaluation is based on analysis of tissue loading during simulated standing on one leg; FEA the computational time for design and evaluation is currently 12 minutes” corresponds to claim limitation “simulating a dynamic use event to determine the loading pressure includes”.
It has been disclosed in page 8 under section II H.: “The FEA based design and evaluation procedure consists of 5 steps which are schematically illustrated in Fig. 9 … Once the liner or socket are designed by the fitting pressures and in their second generation (γ = 2) they are able to develop stresses. The use of multi-generation materials in this way therefore forms a simple means of driving the designs of the liner and socket and simultaneously provides a means to simulate the pre-loading induced by donning. In step 1 only the soft tissues are developing significant stresses (γliner = 1, γsocket = 1), liner fitting pressures are applied loading and deforming the limb and freely morphing and carrying the liner source geometry with it to its desired design. In step 2 the liner material is assigned with its natural mechanical properties (γliner = 2, γsocket = 1). The liner starts out stress free in its equilibrium shape but, as the liner fitting pressures are ramped down, the tissue experiences some relaxation and starts to push against the liner, deforming it until the tissue and liner reach equilibrium. Steps 1 and 2 therefore function to design and don the liner … In step 3 only the liner and soft tissues are able to develop significant stresses (γliner = 2, γsocket = 1) and the socket fitting pressures are applied to the skin surface. The socket fitting pressures deform the limb and the liner, and morph and carry the socket to its desired design.” Therefore, Kevin teaches loading pressure determined, being applied to the biological body segment by the biomechanical interface in the initial configuration/design (e.g., soft tissues developed significant stresses (γliner = 1, γsocket = 1), liner fitting pressures are applied loading and deforming the limb and carrying the liner source geometry with it to its desired design; soft tissues are able to develop significant stresses (γliner = 2, γsocket = 1) and the socket fitting pressures are applied to the skin surface)).
Kevin teaches comparing the determined loading pressure to a physiological tolerance; (Kevin disclosed in page 7 left col.: “Fig. 7A-B show typically reported vulnerable and safe regions for loading. Since palpation assesses a combination of local tissue stiffness and thickness (i.e. distance to bones), this assessment is here termed displaceability, i.e. the ability of the tissue to locally deform when loaded. A prosthetists design map is therefore based on experience and palpation. To create an automated assessment of displaceability FEA is used here. Displaceability is computed as the magnitude of skin surface displacement following the application of a homogenous pressure of 90 kPa (i.e. the response to the liner fitting pressure is used here). Fig. 7C shows FEA derived relative displaceability data (normalized total displacement). Reported vulnerable and safe regions are seen to correlate well with regions with low and high displaceability respectively. Fig. 7D shows that the displaceability data can also be mapped onto the socket elements (based on nearest neighbor interpolation). This mapped data can be used as a displaceability based design map to control socket design features.”
The displaceability in above disclosure corresponds with a physiological tolerance).
and Kevin teaches in the three-dimensional FEA model, varying at least one of a compliance or a geometry of the biomechanical interface based on the comparison of the determined loading pressure and the physiological tolerance to thereby obtain a final configuration of the biomechanical interface; (Kevin disclosed in page 6-8 under section II G.: “A design map is defined, denoted by D, with D ∈ [0, 1], which can be used to set the local socket fitting pressure and local socket element stiffness through a linear mapping. The spatially varying fitting pressures P for each triangular skin surface element can be determined using: P = pmin + D (pmax − pmin). Here pmax and pmin are the desired minimum and maximum fitting pressures. For the spatially varying mechanical properties of the socket the constitutive parameters c for each socket element C can then be derived from: C = cmin + D (cmax − cmin) Here cmax and cmin are the desired minimum and maximum c values … For iterative design optimization procedures the design map D can be made to evolve with each iteration and a different design map can be employed for the fitting pressure and the socket materials ... The design map in Fig. 7D is denoted D123. Fig. 7E is a variation of this design map where the design map was reduced for elements close to the fibular head and distal end of the tibia … This adjusted design map is denoted D4, and can be viewed as the result of one manual design iteration with respect to the mapping D123. Both design maps have also been nulled at the cut-line rim (10 mm high) to create a comfortable rim (as nulled regions result in compliant materials and low fitting pressures)).”
The disclosure above “A design map is defined, denoted by D, with D ∈ [0, 1], … the spatially varying fitting pressures P for each triangular skin surface element can be determined; For iterative design optimization procedures the design map D can be made to evolve with each iteration and a different design map can be employed for the fitting pressure and the socket materials; Both design maps have also been nulled at the cut-line rim (10 mm high) to create a comfortable rim (as nulled regions result in compliant materials and low fitting pressures” correspond to claim limitation “varying at least one of a compliance or a geometry of the biomechanical interface based on the comparison of the determined loading pressure”.
Further, it has been disclosed in page 9 under section III A.: “Fig. 3 shows the data-driven and automated design and computational modeling framework for development of patient-specific sockets and liners … The outcome of the framework is a set of CAD files allowing for computer aided manufacture.” It has been shown in Fig. 3(B) the patient-specific geometry is obtained using anatomical landmarks the socket cut-lines can be automatically created in Fig. 3(C), spatially varying design features, such as socket compliance and fitting pressure, defined using FEA based measures of tissue vulnerability in Fig. 3(F), fitting pressure fields can be used to morph the liner and socket into their desired shape, while also pre-loading the tissue due to donning in Fig. 3(G). The designs can now be evaluated for body weight loading in Fig. 3(H), and optimal designs can be exported in Fig. 3(I), for 3D printing-based manufacturing in Fig. 3(J)).
wherein Kevin teaches determining the loading pressure includes determining at least two loading pressures and wherein varying at least one of the compliance or the geometry includes reducing a variance between the at least two loading pressures. (Examiner notes that the claim language includes two optional embodiments, a first embodiment “varying at least one of the compliance” "or" a second embodiment “the geometry includes reducing a variance”. Since "and/or" is interpreted as at least one of, only one of the two embodiments need to be taught by the reference.
Kevin disclosed in page 6-7 under section II G.: “A design map is defined, denoted by D, with D ∈ [0, 1], which can be used to set the local socket fitting pressure and local socket element stiffness through a linear mapping. The spatially varying fitting pressures P for each triangular skin surface element can be determined … Here pmax and pmin are the desired minimum and maximum fitting pressures … the current 3D printer only 5 compliant material types are available (see Table I). By using the design map the spatial variation of fitting pressure and socket material parameters can each be controlled with two parameters (a desired minimum and a maximum). … Displaceability is computed as the magnitude of skin surface displacement following the application of a homogenous pressure of 90 kPa (i.e., the response to the liner fitting pressure is used here) … Fig. 7E is a variation of this design map where the design map was reduced for elements close to the fibular head and distal end of the tibia. This reduction was informed by the fact that high pressures are observed here for simulations with the mapping D123.” In page 10-11 disclosed: “Fig. 13 it can be observed that a rigid socket design based on a homogeneous socket fitting pressure (design 1) … high pressures remain at the lower portion of the fibular head and the region close to the distal end of the tibia. By utilizing not only spatially varying fitting pressures but also compliant materials such as in design 3, the contact pressure at the front of the tibia can be further reduced … If based on these findings the socket material stiffness and fitting pressures are reduced further for these regions (design 4), these observed pressures can be reduced. These results show the possible benefit, …”.
From the above disclosure, it is understood that Kevin teaches the claim limitation “determining the loading pressure includes determining at least two loading pressures and wherein varying at least reducing a variance between the two loading pressures” (e.g., in Fig. 13, a rigid socket design based on a homogeneous socket fitting pressure; by utilizing spatially varying fitting pressures and also compliant materials such as in design 3, the contact pressure at the front of the tibia can be further reduced)).
However, Kevin doesn’t explicitly teach the limitation “varying at least a geometry of the biomechanical interface based on the physiological tolerance”.
Lee teaches varying at least a geometry of the biomechanical interface based on the physiological tolerance. (Lee disclosed in page 5 under ‘Methods’ (at last para): “A finite element model was built, based on the limb geometry and pain threshold recorded in the indentation test of Subject 1 (Table 1), to simulate the indentation process so that the stress distribution and indention depth of the different test sites beneath the indenting material could be studied … Pressure, with magnitude equivalent to the measured pain threshold of each test site, was applied to the indenter to load against the corresponding test site.” In page 7-8 under ‘Discussion’: “In this investigation, focus was put on the residual limb measuring the pain threshold and tolerance of different regions of the residual limbs of trans-tibial amputees. … Throughout the process of prosthetic design optimization, a prosthesis should be made to prevent the applied loads at the socket-limb interface during the gait cycle exceeding a level with reference to its pain threshold … In addition to average pressure that the tissue can withstand, the pressure distribution underlying the indenter and the soft tissue distortion when pain was just initiated were studied using FE modeling. The FE model shows that the peak interface pressure at the same test site indented with different stiffness of material were very close at the point when pain is triggered. … The subjects could tolerate greater load with Pelite® because it induces less average pressure, and more importantly the peak pressure, at the skin surface and around the edge of indenter, hence allowing higher indenting load to be applied before the peak pressure reaches the threshold. … In addition to stress at the skin surface, stress developed deep within the tissues is also an important parameter when discussing pain … We have established a FE model to investigate the load transfer at the limb-socket interface.”
It has been discussed above that a finite element model (FE model) was built, based on the limb geometry and pain threshold recorded in the indentation test of Subject 1, where the pressure, with magnitude equivalent to the measured pain threshold of each test site, was applied to the indenter to load against the corresponding test site. This is the example corresponds to the claim limitation “geometry of the biomechanical interface can be varied based on the pressure of biomechanical interface and the physiological tolerance.” A FE model is established to investigate the load transfer at the limb-socket interface, which is a useful tool for the prediction of the stress distribution at the interface and provide better understanding of the effects of socket, i.e., biomechanical interface modifications. Therefore, Lee teaches the abovementioned claim limitation).
Kevin and Lee are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin and Lee to modify determining loading pressure and desired value of the biomechanical interface to the biological body segment of Kevin, to include comparing loading pressure of the biomechanical interface to the physiological tolerance of Lee. The suggestion/motivation for doing so would have been obvious by Lee because “The presented framework will benefit amputees as it offers a 14 fully data-driven and patient-specific design procedure. Due to the computational efficiency achieved, the framework can be combined with iterative design optimization. Through the use of FEA based evaluation, or virtual prototyping. By making the entire design and fabrication process repeatable and data-driven, the prosthetic device manufacturing process can be based on a scientific rationale, whereby the comfort outcomes can be clearly linked to design choices.” (Lee disclosed in page 13-14 under section IV).
Neither, Kevin nor Lee explicitly teaches the limitation “creating a compound model of internal and external features of the biological body segment using imaging markers attached to the biological body segment to guide a point cloud alignment algorithm between external features detected using photogrammetric imaging of the biological body segment and internal features detected using non-invasive imaging of the biological body segment;
Zheng teaches creating a compound model of internal and external features of the biological body segment using imaging markers attached to the biological body segment to guide a point cloud alignment algorithm between external features detected using photogrammetric imaging of the biological body segment and internal features detected using non-invasive imaging of the biological body segment; (Zheng disclosed in page 72 section 5: “The process for registration using ‘one or three-point registration’ begins by importing multiple, independent models into the workspace. … It means we can define one or three points in each model. … Here, each point has three coordinates (x, y, z). In this case, to match the bones model and the skin model, we defined three points in each model; … Here, we set the skin model as a fixed object and made bones object floating. By doing so, the software computed the rotation and aligned the bones model using the reference points we had selected. Immediately, models of bones and skin were registered successfully, we saved them as an integral model that represented the combination of every model in their desired positions. The matching method in the Geomagic provided a quick shortcut to matching multiple models into an integral model while retaining the desired spatial position. The complete 3D model of the residual limb can be generated, as show in Fig. 9.” The completed model which integrates the bones and skin (in figure 9) is a compound model with both internal and external features.
Further, in page 72-73 section 7: “This article addresses an innovative reverse engineering application for 3D reconstruction of residual limb. The study has demonstrated that the integration of CT scanning, image processing and NURBS surface fitting from a cloud of points can be successfully applied to complex bony structure reconstruction. … In addition, the 3D reconstruction is a digitalized approach; the residual limb’s bony and skin model can be used to generate FEA meshes and prosthetic socket design analysis.”).
Kevin, Lee and Zheng are analogous art because they are related to design Biomechanical interfaces or prosthetic socket design. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee and Zheng, to modify generating 3D FEA model of Biomechanical interfaces of Kevin, to include the teaching of Zheng to guide a point cloud while using internal and external features of the biological body segment by implementing photogrammetric and non-invasive imaging to create a compound model. The suggestion/motivation for doing so would have been obvious by Zheng because “Aiming at overcoming the limitations of the plaster-casting method in traditional prosthetic socket fabrication, the idea of reconstructing the 3D models for bones and skin of the residual limb is proposed. Given the two-dimensional obtained image through CT scanning, using image processing and reverse engineering techniques, the 3D solid model of the residual limb can be successfully reconstructed. The new approach can reproduce both the internal and the external structure of the residual limb. It can moreover avoid making a positive mould by the way of manual modifications. In addition to this, it can provide a scientific basis for the individualization of prosthetic socket design.” (Zheng disclosed in page ‘Abstract’).
Regarding claim 128, Kevin, Lee and Zheng teach the method of claim 127, further Kevin teaches iteratively determining the loading pressure of the biomechanical interface to at least one region of the biological body segment using the three-dimensional FEA model, and varying at least one of the compliance or the geometry of the biomechanical interface until the determined loading pressure is below the physiological tolerance. (Kevin disclosed in page 7 under section II G.: “The liner fitting pressure was set at a homogeneous 90 kPa. This pressure was manually determined by varying it until the mean skin surface pressure was qualitatively observed to be approximately 15 kPa, which was deemed a target donned liner skin surface pressure … A design map is defined, denoted by D, with D ∈ [0, 1], which can be used to set the local socket fitting pressure and local socket element stiffness through a linear mapping. The spatially varying fitting pressures P for each triangular skin surface element can be determined … For iterative design optimization procedures the design map D can be made to evolve with each iteration and a different design map can be employed for the fitting pressure and the socket materials” The liner fitting pressure was manually determined by varying it until the mean skin surface pressure was qualitatively observed at a target donned liner skin surface pressure, is considered as loading pressure applied to one region of the biological body segment. Further, it has been disclosed in page 10 section IV (at left col.): “Since FEA-based design and design evaluation takes place in 12 minutes, the framework opens the door to iterative FEA based socket and liner design optimization. For optimization, the design controlling parameters can be updated in an iterative fashion while minimizing measures predictive of comfort, such as skin contact pressure and tissue strain.” Further, it has been discussed in page 3 under section II A.: 3D patient-specific FEA models can be constructed, used to generate custom liner and socket designs (shown in Fig. 3).
Therefore, Kevin teaches the loading pressure of the biomechanical interface being determined iteratively and the design controlling parameters can be updated/varied in an iterative fashion while minimizing the pain tolerance such as measuring predictive of comfort, skin contact pressure and tissue strain etc. Therefore, Kevin teaches the limitation: the geometry of the biomechanical interface is updated until the determined loading pressure is below the tolerance or desired value).
Kevin teaches comparing the determined loading pressure to the physiological tolerance; (Kevin disclosed in page 7 left col.: “Fig. 7A-B show typically reported vulnerable and safe regions for loading. Since palpation assesses a combination of local tissue stiffness and thickness (i.e. distance to bones), this assessment is here termed displaceability, i.e. the ability of the tissue to locally deform when loaded. A prosthetists design map is therefore based on experience and palpation. To create an automated assessment of displaceability FEA is used here. Displaceability is computed as the magnitude of skin surface displacement following the application of a homogenous pressure of 90 kPa (i.e. the response to the liner fitting pressure is used here). Fig. 7C shows FEA derived relative displaceability data (normalized total displacement). Reported vulnerable and safe regions are seen to correlate well with regions with low and high displaceability respectively. Fig. 7D shows that the displaceability data can also be mapped onto the socket elements (based on nearest neighbor interpolation). This mapped data can be used as a displaceability based design map to control socket design features.” The displaceability in above disclosure corresponds with the physiological tolerance).
Regarding claim 130, Kevin, Lee and Zheng teach the method of claim 127, further Kevin teaches comparing the plurality of loading pressures to a plurality of physiological tolerances. (Kevin disclosed in page 7 left col.: “Fig. 7A-B show typically reported vulnerable and safe regions for loading. Since palpation assesses a combination of local tissue stiffness and thickness (i.e. distance to bones), this assessment is here termed displaceability, i.e. the ability of the tissue to locally deform when loaded. A prosthetists design map is therefore based on experience and palpation. To create an automated assessment of displaceability FEA is used here. Displaceability is computed as the magnitude of skin surface displacement following the application of a homogenous pressure of 90 kPa (i.e. the response to the liner fitting pressure is used here). Fig. 7C shows FEA derived relative displaceability data (normalized total displacement). Reported vulnerable and safe regions are seen to correlate well with regions with low and high displaceability respectively. Fig. 7D shows that the displaceability data can also be mapped onto the socket elements (based on nearest neighbor interpolation). This mapped data can be used as a displaceability based design map to control socket design features.” The displaceability in above disclosure corresponds with the physiological tolerance).
However, Kevin doesn’t explicitly teach the limitation “determining a plurality of loading pressures, each loading pressure of the determined plurality of loading pressures being of a distinct anatomical point or a distinct anatomical region of the biological body segment;”
Lee teaches determining a plurality of loading pressures, each loading pressure of the determined plurality of loading pressures being of a distinct anatomical point or a distinct anatomical region of the biological body segment; (Lee disclosed in page 4-6 under ‘Methods’ and ‘Results’: “The eleven test regions were those which commonly require relieves at prosthetic sockets including tibial tuberosity, mid-shaft of tibia, fibula head, distal ends of fibula and tibia as well as those where relatively high magnitude of force is usually applied as expected for a PTB socket, … Pain threshold and pain tolerance among different test regions, indenting materials and subjects were compared using one way analysis of variance (Bonferrori test). Differences were considered significant at the p<0.05 level … Figure 1 shows the means and standard deviations of pain threshold and pain tolerance over the eleven test regions for all the subjects using indenting materials Pelite® and polypropylene … Greater value of standard deviations over mid-patellar tendon region was due to that subjects 2 and 7 had particularly higher tolerance at MPT than other subjects ... Pain threshold and tolerance over eleven different test sites were averaged for each subject and compared in Table 3 … Figure 3 (a, b) shows the stress distribution pattern at the mid-patellar tendon region of Subject 1 with two indenting materials when pain was initiated … The pressure distribution pattern was similar among different test regions but differed in peak stress values. Table 5 shows the peak interface pressure at skin surface and indentation depth when each test sites was indented with load equivalent to pain threshold.” Therefore, Lee teaches each loading pressure being of a distinct anatomical point or a distinct anatomical region of the biological body segment being determined (e.g., eleven test regions which commonly require relieves at prosthetic sockets including tibial tuberosity, mid-shaft of tibia, fibula head, distal ends of fibula and tibia as well as those where relatively high magnitude of force is usually applied as expected for a PTB socket). Further, the plurality of loading pressures to a plurality of physiological tolerances is compared (e.g., Table 5 shows the peak interface pressure at skin surface and indentation depth when each test sites were indented with load equivalent to pain threshold)).
Kevin and Lee are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin and Lee to modify determining loading pressure and desired value of the biomechanical interface to the biological body segment of Kevin, to include comparing loading pressure of the biomechanical interface to the physiological tolerance of Lee. The suggestion/motivation for doing so would have been obvious by Lee because “The presented framework will benefit amputees as it offers a 14 fully data-driven and patient-specific design procedure. Due to the computational efficiency achieved, the framework can be combined with iterative design optimization. Through the use of FEA based evaluation, or virtual prototyping. By making the entire design and fabrication process repeatable and data-driven, the prosthetic device manufacturing process can be based on a scientific rationale, whereby the comfort outcomes can be clearly linked to design choices.” (Lee disclosed in page 13-14 under section IV).
Regarding claim 131, Kevin, Lee and Zheng teach the method of claim 127, however, Kevin doesn’t explicitly teach the limitation “maximizing a differential between the determined loading pressure and the physiological tolerance for at least two anatomical points or anatomical regions”.
further Lee teaches maximizing a differential between the determined loading pressure and the physiological tolerance for at least two anatomical points or anatomical regions. (Lee disclosed in page 4-6 under ‘Methods’ and ‘Results’: “The eleven test regions were those which commonly require relieves at prosthetic sockets including tibial tuberosity, mid-shaft of tibia, fibula head, distal ends of fibula and tibia as well as those where relatively high magnitude of force is usually applied as expected for a PTB socket, … Pain threshold and pain tolerance among different test regions, indenting materials and subjects were compared using one way analysis of variance (Bonferrori test). … Figure 1 shows the means and standard deviations of pain threshold and pain tolerance over the eleven test regions for all the subjects using indenting materials Pelite® and polypropylene … Greater value of standard deviations over mid-patellar tendon region was due to that subjects 2 and 7 had particularly higher tolerance at MPT than other subjects ... Pain threshold and tolerance over eleven different test sites were averaged for each subject and compared in Table 3 … Figure 3 (a, b) shows the stress distribution pattern at the mid-patellar tendon region of Subject 1 with two indenting materials when pain was initiated … The pressure distribution pattern was similar among different test regions but differed in peak stress values. Table 5 shows the peak interface pressure at skin surface and indentation depth when each test sites was indented with load equivalent to pain threshold.” Therefore, Lee teaches a differential between the determined loading pressure and the physiological tolerance is maximized for two anatomical points or regions (e.g., eleven test regions which commonly require relieves at prosthetic sockets including tibial tuberosity, mid-shaft of tibia, fibula head, distal ends of fibula and tibia as well as those where relatively high magnitude of force is usually applied as expected for a PTB socket. Figure 1 shows the means and standard deviations of pain threshold and pain tolerance over the eleven test regions, Table 5 shows the peak interface pressure at skin surface and indentation depth when each test sites was indented with load equivalent to pain threshold)).
Kevin and Lee are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin and Lee to modify determining loading pressure and desired value of the biomechanical interface to the biological body segment of Kevin, to include comparing loading pressure of the biomechanical interface to the physiological tolerance of Lee. The suggestion/motivation for doing so would have been obvious by Lee because “The presented framework will benefit amputees as it offers a 14 fully data-driven and patient-specific design procedure. Due to the computational efficiency achieved, the framework can be combined with iterative design optimization. Through the use of FEA based evaluation, or virtual prototyping. By making the entire design and fabrication process repeatable and data-driven, the prosthetic device manufacturing process can be based on a scientific rationale, whereby the comfort outcomes can be clearly linked to design choices.” (Lee disclosed in page 13-14 under section IV).
Regarding claim 132, Kevin, Lee and Zheng teach the method of claim 130, however, Kevin doesn’t explicitly teach the limitation “minimizing a variance of a plurality of differentials between the determined plurality of loading pressures and the plurality of physiological tolerances”.
further Lee teaches minimizing a variance of a plurality of differentials between the determined plurality of loading pressures and the plurality of physiological tolerances. (Lee disclosed in page 7-8 section ‘Discussion’: “In this investigation, focus was put on the residual limb measuring the pain threshold and tolerance of different regions of the residual limbs of trans-tibial amputees ... Throughout the process of prosthetic design optimization, a prosthesis should be made to prevent the applied loads at the socket-limb interface during the gait cycle exceeding a level with reference to its pain threshold. Considering that longer exposure can likely reduce the load level that the tissue can tolerate, the pain tolerance and threshold can be taken as a maximum allowable stress that can be applied onto the residual limb such that pain and discomfort would not be initiated … In addition to average pressure that the tissue can withstand, the pressure distribution underlying the indenter and the soft tissue distortion when pain was just initiated were studied using FE modeling. The FE model shows that the peak interface pressure at the same test site indented with different stiffness of material were very close at the point when pain is triggered. … The results that the subjects could withstand higher force with Pelite® than polypropylene can be explained in terms of stress. Softer Pelite® indenting material has the ability to deform when mild to high loading is applied. The deformation can reduce tissue stress by increasing the actual contact area with the tissue and spreading more uniformly the stress applied to the skin.” Therefore, Lee teaches minimization of variance of a plurality of differentials between the determined loading pressures and the physiological tolerances being performed in above disclosure (e.g., Pelite® indenting material has the ability to deform when mild to high loading is applied. The deformation can reduce tissue stress by increasing the actual contact area with the tissue and spreading more uniformly the stress applied to the skin)).
Kevin and Lee are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin and Lee to modify determining loading pressure and desired value of the biomechanical interface to the biological body segment of Kevin, to include comparing loading pressure of the biomechanical interface to the physiological tolerance of Lee. The suggestion/motivation for doing so would have been obvious by Lee because “The presented framework will benefit amputees as it offers a 14 fully data-driven and patient-specific design procedure. Due to the computational efficiency achieved, the framework can be combined with iterative design optimization. Through the use of FEA based evaluation, or virtual prototyping. By making the entire design and fabrication process repeatable and data-driven, the prosthetic device manufacturing process can be based on a scientific rationale, whereby the comfort outcomes can be clearly linked to design choices.” (Lee disclosed in page 13-14 under section IV).
Regarding claim 133, Kevin, Lee and Zheng teach the method of claim 127, however, Kevin doesn’t explicitly teach the limitation “the physiological tolerance is a pain threshold or a pain tolerance”.
wherein Lee teaches the physiological tolerance is a pain threshold or a pain tolerance. (Lee disclosed in page 4 under ‘Introduction’ (last para) and ‘Methods’: “The objective of this study was to evaluate and compare the tissue stress at pain threshold and tolerance limits over different regions of the residual limb among trans-tibial amputees using an indentation method. Tissue strain and stress distribution upon indentation could provide additional information on pain initiation. With the help of finite element analysis, we have investigated the soft tissue displacement as well as the stress distribution beneath the indenter when the tissue was indented to an extent reaching pain.”).
Kevin and Lee are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin and Lee to modify determining loading pressure and desired value of the biomechanical interface to the biological body segment of Kevin, to include comparing loading pressure of the biomechanical interface to the physiological tolerance of Lee. The suggestion/motivation for doing so would have been obvious by Lee because “The presented framework will benefit amputees as it offers a 14 fully data-driven and patient-specific design procedure. Due to the computational efficiency achieved, the framework can be combined with iterative design optimization. Through the use of FEA based evaluation, or virtual prototyping. By making the entire design and fabrication process repeatable and data-driven, the prosthetic device manufacturing process can be based on a scientific rationale, whereby the comfort outcomes can be clearly linked to design choices.” (Lee disclosed in page 13-14 under section IV).
Regarding claim 134, Kevin, Lee and Zheng teach the method of claim 127, wherein Kevin teaches generating the three-dimensional FEA model includes defining a load line of the biological body segment and the biomechanical interface. (Kevin disclosed in page 4 section II D.: “the MRI derived patient geometry is used here. The source geometry for the liner is created by offsetting a layer from the skin surface. For the current study the liner thickness varied linearly from 4 mm to 6 mm from the top of the model to the distal end. Once the liner source geometry is defined the source geometry of the socket is formed by offsetting from the outer surface of the liner source geometry. However, first the socket upper boundary, known as the cut-line, is defined. Automatic cut-line creation is based on anatomical landmarks on the bones (Fig. 5A). The landmarks define curve control points on the outer liner surface (Fig. 5B), … Next, a smooth cubic spline is fitted to the curve control points and mapped to the liner surface to create the cut-line (Fig. 5B)”. It has been discussed in page 3 section II A. (right col.) that Fig. 3 presents an overview of the data-driven computational design framework. It illustrates how, based on MRI (Fig. 3A) and indentation tests (Fig. 3E), 3D and patient-specific FEA models can be constructed, which can be used to generate custom liner and socket designs.
Kevin teaches the three-dimensional FEA model generated (In Fig. 3, 5A, 5B) includes defining a load line of the biological body segment and the biomechanical interface (e.g., the source geometry of the liner socket (as biomechanical interface) is defined by cutline, automatic cut-line creation is based on anatomical landmarks on the bones (Fig. 5A) and the landmarks define curve control points on the outer liner surface (Fig. 5B)).
Regarding claim 135, Kevin, Lee and Zheng teach the method of claim 134, further Kevin teaches defining at least one of a location or an orientation of an alignment component of the biomechanical interface. (Kevin disclosed in page 4 section II D.: “a smooth cubic spline is fitted to the curve control points and mapped to the liner surface to create the cut-line (Fig. 5B). The source geometry for the socket is then formed by offsetting the surface under the cut-line. A uniform socket wall thickness of 6 mm is used here and the socket cut-line rim was rounded with a rounding diameter matching the socket wall thickness. This creates the socket geometry shown in Fig. 5C.” It has been disclosed in page 7-8 under section II G.: “Fig. 7D shows that the displaceability data can also be mapped onto the socket elements (based on nearest neighbor interpolation). This mapped data can be used as a displaceability based design map to control socket design features … The design map in Fig. 7D is denoted D123. Fig. 7E is a variation of this design map where the design map was reduced for elements close to the fibular head and distal end of the tibia. This reduction was informed by the fact that high pressures are observed here for simulations with the mapping D123. This adjusted design map is denoted D4, and can be viewed as the result of one manual design iteration with respect to the mapping D123. Both design maps have also been nulled at the cut-line rim (10 mm high) to create a comfortable rim (as nulled regions result in compliant materials and low fitting pressures).”).
Regarding claim 136, Kevin, Lee and Zheng teach the method of claim 127, further Kevin teaches defining at least two subject states of the biological body segment within the three-dimensional FEA model. (Under BRI, Examiner would construe subject two states of the biological body segment as stress free and stressful scenarios. Kevin disclosed in page 8 section II H.: “The socket, liner, and tissue regions share nodes at each interface, simulating high friction tied interfaces. The liner and socket are each designed and donned in separate 2 step procedures. First fitting pressures are used to morph the geometries into desired designs … Once their desired design is achieved they are assigned with natural mechanical properties in a stress free state. This process of morphing the designs (while the soft tissue is pre-loaded) without developing stresses in the liner or socket regions is achieved by modelling the liner and socket materials as multi-generational materials … Once the liner or socket are designed by the fitting pressures and in their second generation (γ = 2) they are able to develop stresses. … In step 1 only the soft tissues are developing significant stresses (γliner = 1, γsocket = 1), liner fitting pressures are applied loading and deforming the limb and freely morphing and carrying the liner source geometry with it to its desired design.” Further, it has been discussed in page 3 under section II A.: 3D patient-specific FEA models can be constructed, used to generate custom liner and socket designs (shown in Fig. 3).
Kevin teaches two subject states of the biological body segment within the model being defined (e.g., process of morphing the designs (when the soft tissue is pre-loaded without developing stresses in the liner or socket regions is achieved, i.e., soft tissue with stress free state; soft tissues are developing significant stresses (γliner = 1, γsocket = 1), liner fitting pressures are applied loading and deforming the limb, i.e., with soft tissue with significant stresses scenarios).
Regarding claim 137, Kevin, Lee and Zheng teach the method of claim 136, wherein Kevin teaches determining the loading pressure includes determining loading pressures applied to the biological body segment at the at least two subject states. (Under BRI, Examiner would construe subject two states of the biological body segment as stress free and stressful scenarios. Kevin disclosed in page 8 section II H.: “The socket, liner, and tissue regions share nodes at each interface, simulating high friction tied interfaces. The liner and socket are each designed and donned in separate 2 step procedures. First fitting pressures are used to morph the geometries into desired designs … Once their desired design is achieved they are assigned with natural mechanical properties in a stress free state. This process of morphing the designs (while the soft tissue is pre-loaded) without developing stresses in the liner or socket regions is achieved by modelling the liner and socket materials as multi-generational materials … Since during the design phase the material can be made to have negligible stiffness (γ = 1) they remain in an effectively stress free state when the source geometry is morphed into a desired design … Once the liner or socket are designed by the fitting pressures and in their second generation (γ = 2) they are able to develop stresses. … In step 1 only the soft tissues are developing significant stresses (γliner = 1, γsocket = 1), liner fitting pressures are applied loading and deforming the limb and freely morphing and carrying the liner source geometry with it to its desired design.”).
Regarding claim 138, Kevin, Lee and Zheng teach the method of claim 136, wherein Kevin teaches the at least two subject states include a normal state and at least one of a compressed state or an expanded state. (Kevin teaches normal state of biological body segment in page 8 section II H. (e.g., process of morphing the designs (when the soft tissue is pre-loaded without developing stresses in the liner or socket regions is achieved; during the design phase the material can be made to have negligible stiffness (γ = 1) they remain in an effectively stress-free state when the source geometry is morphed into a desired design), (please see claim 137 above). Further, Kevin disclosed in page 5-6 II F.: “residual limbs are known to be capable of changing volume due to loading and with use of sockets, across different time scales … Therefore to allow for realistic pressures and deformations κ`= 18·c was used here, which does allow for some volume change of the tissue … The value for κ` to use in the current study was estimated by altering it such that a similar degree of pressure induced skin displacement was qualitatively observed … For the liner and socket materials the parameters were identified using uniaxial compression experiments …”. Kevin teaches compression experiments (i.e., compressed state) being performed on biological body segment).
Regarding claim 140, Kevin, Lee and Zheng teach the method of claim 127, wherein Kevin teaches simulating the dynamic use event includes simulating a motion event performed in real-time by a subject. (Kevin disclosed in page 9-10 section IV: “This study presents a novel framework for the quantitative design, and computational evaluation, of patient-specific prosthetic liners and sockets for people with lower limb amputations. An overview of the components of the novel framework is presented in Fig. 3 … The design process is automated and driven by patient-specific data. The design is generated and evaluated using FEA. Evaluation is based on analysis of tissue loading during simulated standing on one leg, i.e. the application of a force equivalent to body weight.” In page 9 section III A. (left col.): “Fig. 3 shows the data-driven and automated design and computational modeling framework for development of patient-specific sockets and liners. For FEA the computational time for design and evaluation is currently 12 minutes”).
Regarding claim 141, Kevin, Lee and Zheng teach the method of claim 127, wherein Kevin teaches the three-dimensional FEA model includes a representation of spatially-varying and controllable internal structures of the biomechanical interface. (Kevin disclosed in page 6-7 under section II G.: “The spatially varying fitting pressures P for each triangular skin surface element can be determined using: P = pmin + D(pmax − pmin) Here pmax and pmin are the desired minimum and maximum fitting pressures. For the spatially varying mechanical properties of the socket the constitutive parameters c for each socket element C can then be derived from: C = cmin + D(cmax − cmin). Here cmax and cmin are the desired minimum and maximum c values. In principle the constitutive parameters can be continuously varied between the minimum and maximum level allowing for the creation of smooth parameter variations … By using the design map the spatial variation of fitting pressure and socket material parameters can each be controlled with two parameters (a desired minimum and a maximum).” It has been discussed in page 3 under section II A. that 3D patient-specific FEA models can be constructed, used to generate custom liner and socket designs (shown in Fig. 3)).
Regarding claim 145, Kevin, Lee and Zheng teach the method of claim 127, further Kevin teaches fabricating the biomechanical interface in the final configuration. (Kevin disclosed in page 10 where Fig. 11 shown, Liner manufacturing, the inner surface of the FEA derived liner design (at the end of step 1 of the FEA process) (Fig. 11 (A)) exported to a CAD file (Fig. 11 (B)), which can be 3D printed to serve as a liner mold (Fig. 11 (C)) for silicone liner production (Fig. 11 (D)), after donning the liner on (Fig. 11 (E)) its shape qualitatively resembles that of the liner at the end of step 2 (in Fig. 9) in the FEA process (Fig. 11 (F). Here, the liner of biomechanical interface manufactured, where FEA derived liner design being exported to a CAD file and can be 3D printed serve as a liner mold. When the liner’s shape (after donned liner) on is qualitatively resembles that of the liner at the end of step 2 (in Fig. 9), this scenario is considered as ‘final configuration’ which is fabricated/manufactured (disclosed in Fig. 11) after meeting certain condition in designing biomechanical interface).
Regarding claim 146, Kevin, Lee and Zheng teach the method of claim 145, wherein Kevin teaches fabricating the biomechanical interface includes fabricating spatially-varying and controllable structures comprising the interface. (Kevin disclosed in page 12 in Fig. 12 shown, compliant designs (Fig. 12(A)), an inner socket can be 3D printed with spatially varying stiffness (in 12 (B)), further compliant inner sockets require a rigid outer socket (Fig. 12(C)) which can 3D printed from a single material (Fig. 12(D)). Here, the example in Fig. 12 shown a compliant design of a biomechanical interface, which is fabricated or 3D printed (e.g., inner socket can be 3D printed with spatially varying stiffness (in 12 (B)).
Regarding claim 147, Kevin, Lee and Zheng teach the method of claim 127, however, Kevin and Lee do not explicitly teach the limitation “the non-invasive imaging includes at least one of computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound (US)”.
wherein Zheng teaches the non-invasive imaging includes at least one of computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound (US). (Zheng disclosed in page 69 section 3.2 (right col.): “After image processing, the next step is contour extraction. The so-called contour extraction is meant to extract the bony structure from the images and then reconstruct a 3D representation object. We used a software called Mimics to accomplish the contour extraction. Mimics is an image-processing software package interfacing medical or technical scanner (mostly a CAT or CT scanner) with Rapid Prototyping (RP) or CAD systems. … Mimics is an interactive tool for the visualization and (1) segmentation of CT images as well as 3D rendering of objects.”).
Kevin, Lee and Zheng are analogous art because they are related to design Biomechanical interfaces or prosthetic socket design. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee and Zheng, to modify generating 3D FEA model of Biomechanical interfaces of Kevin, to include the teaching of Zheng to guide a point cloud while using internal and external features of the biological body segment by implementing photogrammetric and non-invasive imaging to create a compound model. The suggestion/motivation for doing so would have been obvious by Zheng because “Aiming at overcoming the limitations of the plaster-casting method in traditional prosthetic socket fabrication, the idea of reconstructing the 3D models for bones and skin of the residual limb is proposed. Given the two-dimensional obtained image through CT scanning, using image processing and reverse engineering techniques, the 3D solid model of the residual limb can be successfully reconstructed. The new approach can reproduce both the internal and the external structure of the residual limb. It can moreover avoid making a positive mould by the way of manual modifications. In addition to this, it can provide a scientific basis for the individualization of prosthetic socket design.” (Zheng disclosed in page ‘Abstract’).
Regarding claim 148, Kevin, Lee and Zheng teach the method of claim 127, however, Kevin and Lee do not explicitly teach the limitation “the photogrammetric imaging includes at least one of digital image correlation (DIC) or handheld scanning tools”.
wherein Zheng teaches the photogrammetric imaging includes at least one of digital image correlation (DIC) or handheld scanning tools. (Zheng disclosed in page 69 section 3.2 (right col.): “After image processing, the next step is contour extraction. The so-called contour extraction is meant to extract the bony structure from the images and then reconstruct a 3D representation object. We used a software called Mimics to accomplish the contour extraction. Mimics is an image-processing software package interfacing medical or technical scanner (mostly a CAT or CT scanner) with Rapid Prototyping (RP) or CAD systems. … Mimics is an interactive tool for the visualization and (1) segmentation of CT images as well as 3D rendering of objects.”).
Kevin, Lee and Zheng are analogous art because they are related to design Biomechanical interfaces or prosthetic socket design. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee and Zheng, to modify generating 3D FEA model of Biomechanical interfaces of Kevin, to include the teaching of Zheng to guide a point cloud while using internal and external features of the biological body segment by implementing photogrammetric and non-invasive imaging to create a compound model. The suggestion/motivation for doing so would have been obvious by Zheng because “Aiming at overcoming the limitations of the plaster-casting method in traditional prosthetic socket fabrication, the idea of reconstructing the 3D models for bones and skin of the residual limb is proposed. Given the two-dimensional obtained image through CT scanning, using image processing and reverse engineering techniques, the 3D solid model of the residual limb can be successfully reconstructed. The new approach can reproduce both the internal and the external structure of the residual limb. It can moreover avoid making a positive mould by the way of manual modifications. In addition to this, it can provide a scientific basis for the individualization of prosthetic socket design.” (Zheng disclosed in page ‘Abstract’).
Regarding claim 149, Kevin, Lee and Zheng teach the method of claim 127, wherein Kevin teaches the dynamic use event includes at least one of standing, walking, walking upstairs, or running. (Kevin disclosed in page 9-10 section IV: “This study presents a novel framework for the quantitative design, and computational evaluation, of patient-specific prosthetic liners and sockets for people with lower limb amputations. An overview of the components of the novel framework is presented in Fig. 3 … The design process is automated and driven by patient-specific data. The design is generated and evaluated using FEA. Evaluation is based on analysis of tissue loading during simulated standing on one leg, i.e. the application of a force equivalent to body weight.” In page 9 section III A. (left col.): “Fig. 3 shows the data-driven and automated design and computational modeling framework for development of patient-specific sockets and liners. For FEA the computational time for design and evaluation is currently 12 minutes”).
Regarding claim 150, Kevin, Lee and Zheng teach the method of claim 149, wherein Kevin teaches the dynamic use event is standing. (Kevin disclosed in page 9-10 section IV: “This study presents a novel framework for the quantitative design, and computational evaluation, of patient-specific prosthetic liners and sockets for people with lower limb amputations. An overview of the components of the novel framework is presented in Fig. 3 … The design process is automated and driven by patient-specific data. The design is generated and evaluated using FEA. Evaluation is based on analysis of tissue loading during simulated standing on one leg,).
Claims 142 and 143 are rejected under 35 U.S.C. 103 as being unpatentable over Kevin, Lee and Zheng and further in view of a Research Paper “Fatigue design of a mechanically biocompatible lattice for a proof-of-concept femoral stem” by Sajad Arabnejad Khanoki et al. (hereinafter Sajad, available online 2016).
Regarding claim 142, Kevin, Lee and Zheng each the method of claim 141, however Kevin, Lee and Zheng do not explicitly teach the limitation “the spatially-varying and controllable internal structures comprise a cellular solid.”
Sajad teaches the spatially-varying and controllable internal structures comprise a cellular solid. (Sajad disclosed in page 65 ‘Abstract’: “A methodology is proposed to design a spatially periodic microarchitectured material for a two-dimensional femoral implant under walking gait conditions. The material is composed of a graded lattice with controlled property distribution that minimizes concurrently bone resorption …”. It has been discussed in page 67 and 69 under section 2 and 3 respectively that, a 2D graded cellular implant being designed. In order to generate the lattice, the square and Kagome unit cells being we selected, as representative of bending and stretching dominated topologies. The methodology applied for the design of a 2D graded cellular implant, the lattice is designed to support the cyclic load of walking and is optimized to reduce bone resorption and interface stress. Further, in page 69 section 3 (left col.) it has been discussed that A is the interface area in Equation (11) where failure index F(b) is expressed. In Eq. (11), the interface failure is normalized with its average over the bone implant interface area.
In above disclosure, a 2D graded cellular implant where the lattice is designed to support the cyclic load of walking and is optimized to reduce interface stress, further interface failure is normalized with its average over the bone implant interface area, as discussed/expressed in Equation (11). This corresponds to claim limitation “controllable structures comprise a cellular solid which is internal”.).
Kevin, Lee, Zheng and Sajad are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee, Zheng and Sajad to modify the spatially-varying and controllable internal structures of the biomechanical interface of Kevin, to include the spatially-varying and controllable internal structures comprising cellular solid and lattice of Sajad. The suggestion/motivation for doing so would have been obvious by Sajad because “. Fig. 8 illustrates the macroscopic von Mises stress distribution throughout the square and Kagome lattice implants associated with the loading condition ... The mesh of the macroscopic elements at the vicinity of the implant border has been refined to capture the interface stresses with a higher resolution. ... We can observe almost a uniform stress distribution in the proximal region of the implants; however, there is higher stress gradient at the vicinity of the implant boundary especially for the square lattice implant, …”. (Sajad disclosed in page 75 section 6).
Regarding claim 143, Kevin, Lee and Zheng each the method of claim 141, however Kevin, Lee and Zheng do not explicitly teach the limitation “the spatially-varying and controllable internal structures comprise a lattice.
wherein Sajad teaches the spatially-varying and controllable internal structures comprise a lattice. (Sajad disclosed in page 65 ‘Abstract’: “A methodology is proposed to design a spatially periodic microarchitectured material for a two-dimensional femoral implant under walking gait conditions. The material is composed of a graded lattice with controlled property distribution that minimizes concurrently bone resorption …”. It has been discussed in page 67 and 69 under section 2 and 3 respectively, a 2D graded cellular implant being designed. In order to generate the lattice, the square and Kagome unit cells being we selected, as representative of bending and stretching dominated topologies. The methodology applied for the design of a 2D graded cellular implant, the lattice is designed to support the cyclic load of walking and is optimized to reduce bone resorption and interface stress. Further, in page 69 section 3 (left col.) it has been discussed that A is the interface area in Equation (11) where failure index F(b) is expressed. In Eq. (11), the interface failure is normalized with its average over the bone implant interface area.
In above disclosure, a 2D graded cellular implant where the lattice is designed to support the cyclic load of walking and is optimized to reduce interface stress, further interface failure is normalized with its average over the bone implant interface area, as discussed/expressed in Equation (11). This corresponds to claim limitation “controllable structures comprise a lattice which is internal”.).
Kevin, Lee, Zheng and Sajad are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee, Zheng and Sajad to modify the spatially-varying and controllable internal structures of the biomechanical interface of Kevin, to include the spatially-varying and controllable internal structures comprising cellular solid and lattice of Sajad. The suggestion/motivation for doing so would have been obvious by Sajad because “. Fig. 8 illustrates the macroscopic von Mises stress distribution throughout the square and Kagome lattice implants associated with the loading condition ... The mesh of the macroscopic elements at the vicinity of the implant border has been refined to capture the interface stresses with a higher resolution. ... We can observe almost a uniform stress distribution in the proximal region of the implants; however, there is higher stress gradient at the vicinity of the implant boundary especially for the square lattice implant, …”. (Sajad disclosed in page 75 section 6).
Claim 144 is rejected under 35 U.S.C. 103 as being unpatentable over Kevin, Lee, Zheng and Sajad and further in view of a Ph.D. thesis “Design automation of lattice-based customized orthopedic for loadbearing implants” by Lorenzo Guariento (hereinafter Lorenzo).
Regarding claim 144, Kevin, Lee, Zheng and Sajad teach the method of claim 143, however Kevin, Lee, Zheng and Sajad do not explicitly teach the limitation “the lattice comprises an edge-based lattice, a face-based lattice, or both.”
Lorenzo teaches the lattice comprises an edge-based lattice, a face-based lattice, or both. (Lorenzo disclosed in page 37 section 2.1: “To assess the mechanical properties of the gyroid lattice structure, and to verify the Gibson-Ashby model for cellular materials, a compressive test was simulated … A series of cubic samples with gyroid lattice infill have been designed and virtually tested through FE analyses … The cubic samples, presented in Figure 13, were designed with 50mm edge length and 10mm gyroid cell size;” Therefore, Lorenzo teaches the lattice comprises an edge-based lattice, a face-based lattice, or both).
Therefore, Kevin, Lee, Zheng, Sajad and Lorenzo are analogous art because they are related to perform finite element analysis to design Biomechanical interfaces. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Kevin, Lee, Zheng, Sajad and Lorenzo to modify spatially-varying and controllable internal structures of the biomechanical interface of Kevin and Lee, to include the Additive Manufacturing (AM) allow to model and manufacture porous lightweight cellular metallic structures such as lattice structure of Lorenzo. The suggestion/motivation for doing so would have been obvious by Lorenzo because “The goal of the present Ph.D. is to analyze, optimize and eventually automate the design process of custom orthopedic pelvic implants for load bearing applications, in order to speedup the process and deliver high-performance customized devices in a short time, as well as cut the related cost by reducing the time-to-implant … Ultimately, the objective is to make custom orthopedic implants more and more accessible for patients with severe conditions that would benefit of personalized solutions. (Lorenzo disclosed in page 21 (last paragraph)).
Conclusion
8. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. An NPL “A Variable-Impedance Prosthetic Socket for a Transtibial Amputee Designed from Magnetic Resonance Imaging Data” by David Moinina Sengeh et al. disclosed designing of a variable impedance prosthetic (VIPr) socket for a transtibial amputee using computer aided design and manufacturing (CAD/CAM) processes. Contact interface pressure recorded during the stance phase of several completed gait cycles indicated a 15% and 17% reduction at toe-off and heel strike, respectively, at the fibula head region while the subject used a VIPr socket. The interface pressures between the socket and the residual limb were evaluated with special attention to specific anatomical features including the tibia and fibula head regions. Even though this project combined multiple materials into one socket through 3D printing based on biomechanical information, the final VIPr socket had to be structurally sound to accommodate the dynamic walking activities of an amputee.
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/NUPUR DEBNATH/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
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